import pandas as pd
from joblib import Parallel, delayed
import os
import pefile

class DataLabeler:
    def __init__(self, threat_db_path):
        self.threat_db = pd.read_csv(threat_db_path)
    
    def _extract_metadata(self, file_path):
        """提取用于标注的元数据"""
        try:
            pe = pefile.PE(file_path)
            return {
                'compile_time': pe.FILE_HEADER.TimeDateStamp,
                'imports': len(pe.DIRECTORY_ENTRY_IMPORT)
            }
        except:
            return None
    
    def label_data(self, data_dir, output_csv):
        """自动标注数据"""
        records = []
        
        for file_name in os.listdir(data_dir):
            file_path = os.path.join(data_dir, file_name)
            features = self._extract_metadata(file_path)
            
            if features:
                # 基于威胁情报库匹配标签
                is_malicious = self._check_threat_intelligence(features)
                records.append({
                    'file_name': file_name,
                    'is_malicious': int(is_malicious),
                    **features
                })
        
        pd.DataFrame(records).to_csv(output_csv, index=False)
    
    def _check_threat_intelligence(self, features):
        """匹配威胁情报特征"""
        # 实现实际的威胁情报匹配逻辑
        return features['imports'] > 30  # 示例简单逻辑 